Many machine learning algorithms can be formulated as the minimization of a training criterion which involves (1) \training errors" on each training example and (2) some hype...
We present a novel Bayesian approach to the problem of value function estimation in continuous state spaces. We define a probabilistic generative model for the value function by i...
Test case generation is an expensive, tedious, and errorprone process in software testing. In this paper, test case generation is accomplished using an Extended Finite State Machi...
Recent advances in wireless communications and positioning devices have generated a tremendous amount of interest in the continuous monitoring of spatial queries. However, such app...
Reinforcement learning has been used for training game playing agents. The value function for a complex game must be approximated with a continuous function because the number of ...